Development of cortical microstructure in the preterm human brain

Early Development and Co-Evolution of Microstructural and Functional Brain Connectomes: A Multi-Modal MRI Study in Preterm and Full-Term Infants

Functional networks characterized by coherent neural activity across distributed brain regions have been observed to emerge early in neurodevelopment. Synchronized maturation across regions that relate to functional connectivity (FC) could be partially reflected in the developmental changes in underlying microstructure. Nevertheless, covariation of regional microstructural properties, termed "microstructural connectivity" (MC), and its relationship to the emergence of functional specialization during the early neurodevelopmental period remain poorly understood. We investigated the evolution of MC and FC postnatally across a set of cortical and subcortical regions, focusing on 45 preterm infants scanned longitudinally, and compared to 45 matched full-term neonates as part of the developing Human Connectome Project (dHCP) using direct comparisons of grey-matter connectivity strengths as well as network-based analyses. Our findings revealed a global strengthening of both MC and FC with age, with connection-specific variability influenced by the connection maturational stage. Prematurity at term-equivalent age was associated with significant connectivity disruptions, particularly in FC. During the preterm period, direct comparisons of MC and FC strength showed a positive linear relationship, which seemed to weaken with development. On the other hand, overlaps between MC- and FC-derived networks (estimated with Mutual Information) increased with age, suggesting a potential convergence towards a shared underlying network structure that may support the co-evolution of microstructural and functional systems. Our study offers novel insights into the dynamic interplay between microstructural and functional brain development and highlights the potential of MC as a complementary descriptor for characterizing brain network development and alterations due to perinatal insults such as premature birth.

The impact of socio-environmental factors on brain structure over the early life course of preterm-born individuals - A systematic review

BACKGROUND

Approximately 11 % of births worldwide are preterm (<37 weeks). While research traditionally focuses on complications of prematurity and brain development, the role of socio-environmental factors has received less attention. Recent studies indicate these factors significantly influence neurocognitive outcomes and brain development, beyond prematurity alone. This review examines the impact of socio-environmental factors on brain structure and function in preterm-born individuals from birth to early adulthood.

METHOD

We conducted searches in PubMed, Embase, and Web of Science for studies up to August 28th, 2024, examining socio-environmental effects on brain structure or function in preterm-born individuals using magnetic resonance imaging. From 891 articles screened, 23 met the inclusion criteria.

RESULTS

Socio-environmental factors, including socioeconomic status, prenatal conditions, hospital environment, and early life experiences, notably affect brain structures in preterm-born individuals. Key impacts were found in limbic and associative cortices (e.g., cingulate gyrus, parieto-temporal cortices), white matter tracts involved in executive functioning (e.g., superior longitudinal fasciculus, cingulum), and overall brain volume. Most studies focused on infancy, with 18 of 23 presenting data from the first year of life.

CONCLUSION

Socio-environmental factors are associated with changes in grey and white matter in the brain, especially in the limbic system and associative areas. These findings underscore the influence of early environments on preterm-born brain development, but long-term impacts remain unclear due to limited data beyond infancy.

Regional Changes in the Fetal Telencephalic Wall Diffusion Metrics Across Late Second and Third Trimesters

During the second and third trimesters of human gestation, the brain undergoes rapid neurodevelopment thanks to critical processes such as neuronal migration, radial glial scaffolding, and synaptic sprouting. Unfortunately, gathering high-quality MRI data on the healthy fetal brain is complex, making it challenging to understand this development. To address this issue, we conducted a study using motion-corrected diffusion tensor imaging (DTI) to analyze changes in the cortical gray matter (CP) and sub-cortical white matter (scWM) microstructure in 44 healthy fetuses between 23 and 36 weeks of gestational age. We automatically segmented these two tissues and parcellated them into eight regions based on anatomy, including the frontal, parietal, occipital, and temporal lobes, cingulate, sensory and motor cortices, and the insula. We were able to observe distinct patterns of diffusion MRI signals across these regions. Specifically, we found that in the CP, fractional anisotropy (FA) consistently decreased with age, while mean diffusivity (MD) followed a downward-open parabolic trend. Conversely, in the scWM, FA exhibited an upward-open parabolic trajectory, while MD followed a downward-open parabolic trend. Our study underscores the potential for diffusion as a biomarker for normal and abnormal neurodevelopment before birth, especially since most neurodiagnostic tools are not yet available at this stage.

Predilection for Perplexion: Preoperative microstructural damage is linked to postoperative delirium

Postoperative delirium is the most common postsurgical complication in older adults and is associated with an increased risk of long-term cognitive decline and Alzheimer's disease (AD) and related dementias (ADRD). However, the neurological basis of this increased risk-whether postoperative delirium unmasks latent preoperative pathology or leads to AD-relevant pathology after perioperative brain injury-remains unclear. Recent advancements in neuroimaging techniques now enable the detection of subtle brain features or damage that may underlie clinical symptoms. Among these, Neurite Orientation Dispersion and Density Imaging (NODDI) can help identify microstructural brain damage, even in the absence of visible macro-anatomical abnormalities. To investigate potential brain microstructural abnormalities associated with postoperative delirium and cognitive function, we analyzed pre- and post-operative diffusion MRI data from 111 patients aged ≥60 years who underwent non-cardiac/non-intracranial surgery. Specifically, we investigated preoperative variation in diffusion metrics within the posterior cingulate cortex (PCC), a region in which prior work has identified glucose metabolism alterations in the delirious brain, and a key region in the early accumulation of amyloid beta (Aβ) in preclinical AD. We also examined the relationship of preoperative PCC NODDI abnormalities with preoperative cognitive function. Compared to patients who did not develop postoperative delirium (n=99), we found increased free water (FISO) and neurite density index (NDI) and decreased orientation dispersion index (ODI) in the dorsal PCC before surgery among those who later developed postoperative delirium (n=12). These FISO differences before surgery remained present at six weeks postoperatively, while these NDI and ODI differences did not. Preoperative dorsal PCC NDI and ODI values were also positively associated with preoperative attention/concentration performance, independent of age, education level, and global brain atrophy. Yet, these diffusion metrics were not correlated with cerebrospinal fluid Aβ positivity or levels. These results suggest that preoperative latent brain abnormalities within the dorsal PCC may underlie susceptibility to postoperative delirium, independent of AD-related (i.e., Aβ) neuropathology. Furthermore, these preoperative microstructural differences in the dorsal PCC were linked to preoperative deficits in attention/concentration, a core feature of postoperative delirium. Our findings highlight microstructural vulnerability within the PCC, a key region of the default mode network, as a neuroanatomic locus that can help explain the link between preoperative attention/concentration deficits and increased postoperative delirium risk among vulnerable older surgical patients.

Sex Differences in Depression: Insights from Multimodal Gray Matter Morphology and Peripheral Inflammatory Factors

Major depressive disorder (MDD) exhibits notable sex differences in prevalence and clinical and neurobiological manifestations. Though the relationship between peripheral inflammation and MDD-related brain changes is well studied, the role of sex as a modifying factor is underexplored. This study aims to assess how sex influences brain and inflammatory markers in MDD. We utilized voxel-based and surface-based morphometry to analyze gray matter (GM) structure, along with GM-based spatial statistics (GBSS) to examine GM microstructure among treatment-naive patients with depression (n = 174) and age-matched healthy controls (n = 133). We uncovered sex-by-diagnosis interactions in several limbic system structures, the frontoparietal operculum and temporal regions. Post hoc analyses revealed that male patients exhibit pronounced brain abnormalities, while no significant differences were noted in females despite their higher depressive scores. Additionally, heightened inflammation levels in MDD were observed in both sexes, with sex-specific effects on sex-specific brain phenotypes, particularly including a general negative correlation in males. Intriguingly, mediation analyses highlight the specific role of the parahippocampal gyrus (PHG) in mediating interleukin (IL)-8 and depression in men. The findings suggest that in clinical practice, it would be beneficial to prioritize sex-specific assessments and interventions for MDD. This includes recognizing the possibility that male patients may experience significant brain alterations, especially when identifying male patients who may underreport symptoms. Possible limitations encompass a small sample size and the cross-sectional design. In future research, the incorporation of longitudinal studies or diverse populations, while considering illness duration, will enhance our understanding of how inflammation interacts with brain changes in depression.

Chronic Inflammation Offers Hints About Viable Therapeutic Targets for Preeclampsia and Potentially Related Offspring Sequelae

The combination of hypertension with systemic inflammation during pregnancy is a hallmark of preeclampsia, but both processes also convey dynamic information about its antecedents and correlates (e.g., fetal growth restriction) and potentially related offspring sequelae. Causal inferences are further complicated by the increasingly frequent overlap of preeclampsia, fetal growth restriction, and multiple indicators of acute and chronic inflammation, with decreased gestational length and its correlates (e.g., social vulnerability). This complexity prompted our group to summarize information from mechanistic studies, integrated with key clinical evidence, to discuss the possibility that sustained or intermittent systemic inflammation-related phenomena offer hints about viable therapeutic targets, not only for the prevention of preeclampsia, but also the neurobehavioral and other developmental deficits that appear to be overrepresented in surviving offspring. Importantly, we feel that carefully designed hypothesis-driven observational studies are necessary if we are to translate the mechanistic evidence into child health benefits, namely because multiple pregnancy disorders might contribute to heightened risks of neuroinflammation, arrested brain development, or dysconnectivity in survivors who exhibit developmental problems later in life.

Microstructure of the cerebellum and its afferent pathways underpins dystonia in myoclonus dystonia

BACKGROUND AND PURPOSE

Myoclonus dystonia due to a pathogenic variant in SGCE (MYC/DYT-SGCE) is a rare condition involving a motor phenotype associating myoclonus and dystonia. Dysfunction within the networks relying on the cortex, cerebellum, and basal ganglia was presumed to underpin the clinical manifestations. However, the microarchitectural abnormalities within these structures and related pathways are unknown. Here, we investigated the microarchitectural brain abnormalities related to the motor phenotype in MYC/DYT-SGCE.

METHODS

We used neurite orientation dispersion and density imaging, a multicompartment tissue model of diffusion neuroimaging, to compare microarchitectural neurite organization in MYC/DYT-SGCE patients and healthy volunteers (HVs). Neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF) were derived and correlated with the severity of motor symptoms. Fractional anisotropy (FA) and mean diffusivity (MD) derived from the diffusion tensor approach were also analyzed. In addition, we studied the pathways that correlated with motor symptom severity using tractography analysis.

RESULTS

Eighteen MYC/DYT-SGCE patients and 24 HVs were analyzed. MYC/DYT-SGCE patients showed an increase of ODI and a decrease of FA within their motor cerebellum. More severe dystonia was associated with lower ODI and NDI and higher FA within motor cerebellar cortex, as well as with lower NDI and higher ISOVF and MD within the corticopontocerebellar and spinocerebellar pathways. No association was found between myoclonus severity and diffusion parameters.

CONCLUSIONS

In MYC/DYT-SGCE, we found microstructural reorganization of the motor cerebellum. Structural change in the cerebellar afferent pathways that relay inputs from the spinal cord and the cerebral cortex were specifically associated with the severity of dystonia.

Brain age prediction and deviations from normative trajectories in the neonatal connectome

Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age-or brain age gap (BAG)-represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We use resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predict PMA for term and preterm infants. Predicted ages from each modality are correlated. At the network level, nearly all canonical brain networks-even putatively later developing ones-generate accurate PMA prediction. Additionally, BAGs are associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.

Machine-learning based prediction of future outcome using multimodal MRI during early childhood

The human brain undergoes rapid changes from the fetal stage to two years postnatally, during which proper structural and functional maturation lays the foundation for later cognitive and behavioral development. Multimodal magnetic resonance imaging (MRI) techniques, especially structural MRI (sMRI), diffusion MRI (dMRI), functional MRI (fMRI), and perfusion MRI (pMRI), provide unprecedented opportunities to non-invasively quantify these early brain changes at whole brain and regional levels. Each modality offers unique insights into the complex processes of both typical neurodevelopment and the pathological mechanisms underlying psychiatric and neurological disorders. Compared to a single modality, multimodal MRI enhances discriminative power and provides more comprehensive insights for understanding and improving neurodevelopmental and mental health outcomes, particularly in high-risk populations. Machine learning- and deep learning-based methods have demonstrated significant potential for predicting future outcomes using multimodal brain MRI acquired during early childhood. Here, we review the unique characteristics of various MRI techniques for imaging early brain development and describe the common approaches to analyze these modalities. We then discuss machine learning approaches in predicting future neurodevelopmental and clinical outcomes using multimodal MRI information during early childhood, highlighting the potential of identifying biomarkers for early detection and personalized interventions in atypical development.

Comparative utility of MRI and EEG for early detection of cortical dysmaturation after postnatal systemic inflammation in the neonatal rat

BACKGROUND

Exposure to postnatal systemic inflammation is associated with increased risk of brain injury in preterm infants, leading to impaired maturation of the cerebral cortex and adverse neurodevelopmental outcomes. However, the optimal method for identifying cortical dysmaturation is unclear. Herein, we compared the utility of electroencephalography (EEG), diffusion tensor imaging (DTI), and neurite orientation dispersion and density imaging (NODDI) at different recovery times after systemic inflammation in newborn rats.

METHODS

Sprague Dawley rat pups of both sexes received single-daily lipopolysaccharide (LPS; 0.3 mg/kg i.p.; n = 51) or saline (n = 55) injections on postnatal days (P)1, 2, and 3. A subset of these animals were implanted with EEG electrodes. Cortical EEG was recorded for 30 min from unanesthetized, unrestrained pups at P7, P14, and P21, and in separate groups, brain tissues were collected at these ages for ex-vivo MRI analysis (9.4 T) and Golgi-Cox staining (to assess neuronal morphology) in the motor cortex.

RESULTS

Postnatal inflammation was associated with reduced cortical pyramidal neuron arborization from P7, P14, and P21. These changes were associated with dysmature EEG features (e.g., persistence of delta waveforms, higher EEG amplitude, reduced spectral edge frequency) at P7 and P14, and higher EEG power in the theta and alpha ranges at P21. By contrast, there were no changes in cortical DTI or NODDI in LPS rats at P7 or P14, while there was an increase in cortical fractional anisotropy (FA) and decrease in orientation dispersion index (ODI) at P21.

CONCLUSIONS

EEG may be useful for identifying the early evolution of impaired cortical development after early life postnatal systemic inflammation, while DTI and NODDI seem to be more suited to assessing established cortical changes.

Gray matter based spatial statistics framework in the 1-month brain: insights into gray matter microstructure in infancy

The neurodevelopmental epoch from fetal stages to early life embodies a critical window of peak growth and plasticity in which differences believed to be associated with many neurodevelopmental and psychiatric disorders first emerge. Obtaining a detailed understanding of the developmental trajectories of the cortical gray matter microstructure is necessary to characterize differential patterns of neurodevelopment that may subserve future intellectual, behavioral, and psychiatric challenges. The neurite orientation dispersion density imaging (NODDI) Gray-Matter Based Spatial Statistics (GBSS) framework leverages information from the NODDI model to enable sensitive characterization of the gray matter microstructure while limiting partial volume contamination and misregistration errors between images collected in different spaces. However, limited contrast of the underdeveloped brain poses challenges for implementing this framework with infant diffusion MRI (dMRI) data. In this work, we aim to examine the development of cortical microstructure in infants. We utilize the NODDI GBSS framework and propose refinements to the original framework that aim to improve the delineation and characterization of gray matter in the infant brain. Taking this approach, we cross-sectionally investigate age relationships in the developing gray matter microstructural organization in infants within the first month of life and reveal widespread relationships with the gray matter architecture.

Age-dependent functional development pattern in neonatal brain: An fMRI-based brain entropy study

The relationship between brain entropy (BEN) and early brain development has been established through animal studies. However, it remains unclear whether the BEN can be used to identify age-dependent functional changes in human neonatal brains and the genetic underpinning of the new neuroimaging marker remains to be elucidated. In this study, we analyzed resting-state fMRI data from the Developing Human Connectome Project, including 280 infants who were scanned at 37.5-43.5 weeks postmenstrual age. The BEN maps were calculated for each subject, and a voxel-wise analysis was conducted using a general linear model to examine the effects of age, sex, and preterm birth on BEN. Additionally, we evaluated the correlation between regional BEN and gene expression levels. Our results demonstrated that the BEN in the sensorimotor-auditory and association cortices, along the 'S-A' axis, was significantly positively correlated with postnatal age (PNA), and negatively correlated with gestational age (GA), respectively. Meanwhile, the BEN in the right rolandic operculum correlated significantly with both GA and PNA. Preterm-born infants exhibited increased BEN values in widespread cortical areas, particularly in the visual-motor cortex, when compared to term-born infants. Moreover, we identified five BEN-related genes (DNAJC12, FIG4, STX12, CETN2, and IRF2BP2), which were involved in protein folding, synaptic vesicle transportation and cell division. These findings suggest that the fMRI-based BEN can serve as an indicator of age-dependent brain functional development in human neonates, which may be influenced by specific genes.

Cortical microstructural abnormalities in amyotrophic lateral sclerosis: a gray matter-based spatial statistics study

Background

Amyotrophic lateral sclerosis (ALS)-related white-matter microstructural abnormalities have received considerable attention; however, gray-matter structural abnormalities have not been fully elucidated. This study aimed to evaluate cortical microstructural abnormalities in ALS and determine their association with disease severity.

Methods

This study included 34 patients with ALS and 30 healthy controls. Diffusion-weighted data were used to estimate neurite orientation dispersion and density imaging (NODDI) parameters, including neurite density index (NDI) and orientation dispersion index (ODI). We performed gray matter-based spatial statistics (GBSS) in a voxel-wise manner to determine the cortical microstructure difference. We used the revised ALS Functional Rating Scale (ALSFRS-R) to assess disease severity and conducted a correlation analysis between NODDI parameters and ALSFRS-R.

Results

In patients with ALS, the NDI reduction involved several cortical regions [primarily the precentral gyrus, postcentral gyrus, temporal cortex, prefrontal cortex, occipital cortex, and posterior parietal cortex; family-wise error (FWE)-corrected P<0.05]. ODI decreased in relatively few cortical regions (including the precentral gyrus, postcentral gyrus, prefrontal cortex, and inferior parietal lobule; FWE-corrected P<0.05). The NDI value in the left precentral and postcentral gyrus was positively correlated with the ALS disease severity (FWE-corrected P<0.05).

Conclusions

The decreases in NDI and ODI involved both motor-related and extra-motor regions and indicated the presence of gray-matter microstructural impairment in ALS. NODDI parameters are potential imaging biomarkers for evaluating disease severity in vivo. Our results showed that GBSS is a feasible method for identifying abnormalities in the cortical microstructure of patients with ALS.

A shifting role of thalamocortical connectivity in the emergence of cortical functional organization

The cortical patterning principle has been a long-standing question in neuroscience, yet how this translates to macroscale functional specialization in the human brain remains largely unknown. Here we examine age-dependent differences in resting-state thalamocortical connectivity to investigate its role in the emergence of large-scale functional networks during early life, using a primarily cross-sectional but also longitudinal approach. We show that thalamocortical connectivity during infancy reflects an early differentiation of sensorimotor networks and genetically influenced axonal projection. This pattern changes in childhood, when connectivity is established with the salience network, while decoupling externally and internally oriented functional systems. A developmental simulation using generative network models corroborated these findings, demonstrating that thalamic connectivity contributes to developing key features of the mature brain, such as functional segregation and the sensory-association axis, especially across 12-18 years of age. Our study suggests that the thalamus plays an important role in functional specialization during development, with potential implications for studying conditions with compromised internal and external processing.

Profiling cortical morphometric similarity in perinatal brains: Insights from development, sex difference, and inter-individual variation

The topological organization of the macroscopic cortical networks important for the development of complex brain functions. However, how the cortical morphometric organization develops during the third trimester and whether it demonstrates sexual and individual differences at this particular stage remain unclear. Here, we constructed the morphometric similarity network (MSN) based on morphological and microstructural features derived from multimodal MRI of two independent cohorts (cross-sectional and longitudinal) scanned at 30-44 postmenstrual weeks (PMW). Sex difference and inter-individual variations of the MSN were also examined on these cohorts. The cross-sectional analysis revealed that both network integration and segregation changed in a nonlinear biphasic trajectory, which was supported by the results obtained from longitudinal analysis. The community structure showed remarkable consistency between bilateral hemispheres and maintained stability across PMWs. Connectivity within the primary cortex strengthened faster than that within high-order communities. Compared to females, male neonates showed a significant reduction in the participation coefficient within prefrontal and parietal cortices, while their overall network organization and community architecture remained comparable. Furthermore, by using the morphometric similarity as features, we achieved over 65 % accuracy in identifying an individual at term-equivalent age from images acquired after birth, and vice versa. These findings provide comprehensive insights into the development of morphometric similarity throughout the perinatal cortex, enhancing our understanding of the establishment of neuroanatomical organization during early life.

Brain age predicted using graph convolutional neural network explains neurodevelopmental trajectory in preterm neonates

OBJECTIVES

Dramatic brain morphological changes occur throughout the third trimester of gestation. In this study, we investigated whether the predicted brain age (PBA) derived from graph convolutional network (GCN) that accounts for cortical morphometrics in third trimester is associated with postnatal abnormalities and neurodevelopmental outcome.

METHODS

In total, 577 T1 MRI scans of preterm neonates from two different datasets were analyzed; the NEOCIVET pipeline generated cortical surfaces and morphological features, which were then fed to the GCN to predict brain age. The brain age index (BAI; PBA minus chronological age) was used to determine the relationships among preterm birth (i.e., birthweight and birth age), perinatal brain injuries, postnatal events/clinical conditions, BAI at postnatal scan, and neurodevelopmental scores at 30 months.

RESULTS

Brain morphology and GCN-based age prediction of preterm neonates without brain lesions (mean absolute error [MAE]: 0.96 weeks) outperformed conventional machine learning methods using no topological information. Structural equation models (SEM) showed that BAI mediated the influence of preterm birth and postnatal clinical factors, but not perinatal brain injuries, on neurodevelopmental outcome at 30 months of age.

CONCLUSIONS

Brain morphology may be clinically meaningful in measuring brain age, as it relates to postnatal factors, and predicting neurodevelopmental outcome.

CLINICAL RELEVANCE STATEMENT

Understanding the neurodevelopmental trajectory of preterm neonates through the prediction of brain age using a graph convolutional neural network may allow for earlier detection of potential developmental abnormalities and improved interventions, consequently enhancing the prognosis and quality of life in this vulnerable population.

KEY POINTS

•Brain age in preterm neonates predicted using a graph convolutional network with brain morphological changes mediates the pre-scan risk factors and post-scan neurodevelopmental outcomes. •Predicted brain age oriented from conventional deep learning approaches, which indicates the neurodevelopmental status in neonates, shows a lack of sensitivity to perinatal risk factors and predicting neurodevelopmental outcomes. •The new brain age index based on brain morphology and graph convolutional network enhances the accuracy and clinical interpretation of predicted brain age for neonates.

Development of neonatal connectome dynamics and its prediction for cognitive and language outcomes at age 2

The functional brain connectome is highly dynamic over time. However, how brain connectome dynamics evolves during the third trimester of pregnancy and is associated with later cognitive growth remains unknown. Here, we use resting-state functional Magnetic Resonance Imaging (MRI) data from 39 newborns aged 32 to 42 postmenstrual weeks to investigate the maturation process of connectome dynamics and its role in predicting neurocognitive outcomes at 2 years of age. Neonatal brain dynamics is assessed using a multilayer network model. Network dynamics decreases globally but increases in both modularity and diversity with development. Regionally, module switching decreases with development primarily in the lateral precentral gyrus, medial temporal lobe, and subcortical areas, with a higher growth rate in primary regions than in association regions. Support vector regression reveals that neonatal connectome dynamics is predictive of individual cognitive and language abilities at 2  years of age. Our findings highlight network-level neural substrates underlying early cognitive development.

Brain age prediction and deviations from normative trajectories in the neonatal connectome

Structural and functional connectomes undergo rapid changes during the third trimester and the first month of postnatal life. Despite progress, our understanding of the developmental trajectories of the connectome in the perinatal period remains incomplete. Brain age prediction uses machine learning to estimate the brain's maturity relative to normative data. The difference between the individual's predicted and chronological age-or brain age gap (BAG)-represents the deviation from these normative trajectories. Here, we assess brain age prediction and BAGs using structural and functional connectomes for infants in the first month of life. We used resting-state fMRI and DTI data from 611 infants (174 preterm; 437 term) from the Developing Human Connectome Project (dHCP) and connectome-based predictive modeling to predict postmenstrual age (PMA). Structural and functional connectomes accurately predicted PMA for term and preterm infants. Predicted ages from each modality were correlated. At the network level, nearly all canonical brain networks-even putatively later developing ones-generated accurate PMA prediction. Additionally, BAGs were associated with perinatal exposures and toddler behavioral outcomes. Overall, our results underscore the importance of normative modeling and deviations from these models during the perinatal period.

White and Gray Matter Abnormality in Burning Mouth Syndrome Evaluated with Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging

PURPOSE

Burning mouth syndrome (BMS) is defined by a burning sensation or pain in the tongue or other oral sites despite the presence of normal mucosa on inspection. Both psychiatric and neuroimaging investigations have examined BMS; however, there have been no analyses using the neurite orientation dispersion and density imaging (NODDI) model, which provides detailed information of intra- and extracellular microstructures. Therefore, we performed voxel-wise analyses using both NODDI and diffusion tensor imaging (DTI) models and compared the results to better comprehend the pathology of BMS.

METHODS

Fourteen patients with BMS and 11 age- and sex-matched healthy control subjects were prospectively scanned using a 3T-MRI machine using 2-shell diffusion imaging. Diffusion tensor metrics (fractional anisotropy [FA], mean diffusivity [MD], axial diffusivity [AD], and radial diffusivity [RD]) and neurite orientation and dispersion index metrics (intracellular volume fraction [ICVF], isotropic volume fraction [ISO], and orientation dispersion index [ODI]) were retrieved from diffusion MRI data. These data were analyzed using tract-based spatial statistics (TBSS) and gray matter-based spatial statistics (GBSS).

RESULTS

TBSS analysis showed that patients with BMS had significantly higher FA and ICVF and lower MD and RD than the healthy control subjects (family-wise error [FWE] corrected P < 0.05). Changes in ICVF, MD, and RD were observed in widespread white matter areas. Fairly small areas with different FA were included. GBSS analysis showed that patients with BMS had significantly higher ISO and lower MD and RD than the healthy control subjects (FWE-corrected P < 0.05), mainly limited to the amygdala.

CONCLUSION

The increased ICVF in the BMS group may represent myelination and/or astrocytic hypertrophy, and microstructural changes in the amygdala in GBSS analysis indicate the emotional-affective profile of BMS.

Feature similarity gradients detect alterations in the neonatal cortex associated with preterm birth

The early life environment programmes cortical architecture and cognition across the life course. A measure of cortical organisation that integrates information from multimodal MRI and is unbound by arbitrary parcellations has proven elusive, which hampers efforts to uncover the perinatal origins of cortical health. Here, we use the Vogt-Bailey index to provide a fine-grained description of regional homogeneities and sharp variations in cortical microstructure based on feature gradients, and we investigate the impact of being born preterm on cortical development at term-equivalent age. Compared with term-born controls, preterm infants have a homogeneous microstructure in temporal and occipital lobes, and the medial parietal, cingulate, and frontal cortices, compared with term infants. These observations replicated across two independent datasets and were robust to differences that remain in the data after matching samples and alignment of processing and quality control strategies. We conclude that cortical microstructural architecture is altered in preterm infants in a spatially distributed rather than localised fashion.

Development of sensorimotor-visual connectome gradient at birth predicts neurocognitive outcomes at 2 years of age

Functional connectome gradients represent fundamental organizing principles of the brain. Here, we report the development of the connectome gradients in preterm and term babies aged 31-42 postmenstrual weeks using task-free functional MRI and its association with postnatal cognitive growth. We show that the principal sensorimotor-to-visual gradient is present during the late preterm period and continuously evolves toward a term-like pattern. The global measurements of this gradient, characterized by explanation ratio, gradient range, and gradient variation, increased with age (p < 0.05, corrected). Focal gradient development mainly occurs in the sensorimotor, lateral, and medial parietal regions, and visual regions (p < 0.05, corrected). The connectome gradient at birth predicts cognitive and language outcomes at 2-year follow-up (p < 0.005). These results are replicated using an independent dataset from the Developing Human Connectome Project. Our findings highlight early emergent rules of the brain connectome gradient and their implications for later cognitive growth.

Assessment of Gray Matter Microstructural Alterations in Alzheimer's Disease by Free Water Imaging

Background

Cortical neurodegenerative processes may precede the emergence of disease symptoms in patients with Alzheimer's disease (AD) by many years. No study has evaluated the free water of patients with AD using gray matter-based spatial statistics.

Objective

The aim of this study was to explore cortical microstructural changes within the gray matter in AD by using free water imaging with gray matter-based spatial statistics.

Methods

Seventy-one participants underwent multi-shell diffusion magnetic resonance imaging, 11C-Pittsburgh compound B positron emission tomography, and neuropsychological evaluations. The patients were divided into two groups: healthy controls (n = 40) and the AD spectrum group (n = 31). Differences between the groups were analyzed using voxel-based morphometry, diffusion tensor imaging, and free water imaging with gray matter-based spatial statistics.

Results

Voxel-based morphometry analysis revealed gray matter volume loss in the hippocampus of patients with AD spectrum compared to that in controls. Furthermore, patients with AD spectrum exhibited significantly greater free water, mean diffusivity, and radial diffusivity in the limbic areas, precuneus, frontal lobe, temporal lobe, right putamen, and cerebellum than did the healthy controls. Overall, the effect sizes of free water were greater than those of mean diffusivity and radial diffusivity, and the larger effect sizes of free water were thought to be strongly correlated with AD pathology.

Conclusions

This study demonstrates the utility of applying voxel-based morphometry, gray matter-based spatial statistics, free water imaging and diffusion tensor imaging to assess AD pathology and detect changes in gray matter.

Age-Related Alterations in Gray Matter Microstructure in Older People With Remitted Major Depression at Risk for Dementia

Background

Major depressive disorder (MDD) in late life is a risk factor for mild cognitive impairment (MCI) and Alzheimer's disease. However, studies of gray matter changes have produced varied estimates of which structures are implicated in MDD and dementia. Changes in gray matter volume and cortical thickness are macrostructural measures for the microstructural processes of free water accumulation and dendritic spine loss.

Methods

We conducted multishell diffusion imaging to assess gray matter microstructure in 244 older adults with remitted MDD (n = 44), MCI (n = 115), remitted MDD+MCI (n = 61), or without psychiatric disorders or cognitive impairment (healthy control participants; n = 24). We estimated measures related to neurite density, orientation dispersion, and free water (isotropic volume fraction) using a biophysically plausible model (neurite orientation dispersion and density imaging).

Results

Results showed that increasing age was correlated with an increase in isotropic volume fraction and a decrease in orientation dispersion index, which is consistent with neuropathology dendritic loss. In addition, this relationship between age and increased isotropic volume fraction was more disrupted in the MCI group than in the remitted MDD or healthy control groups. However, the association between age and orientation dispersion index was similar for all 3 groups.

Conclusions

The findings suggest that the neurite orientation dispersion and density imaging measures could be used to identify biological risk factors for Alzheimer's disease, signifying both conventional neurodegeneration observed with MCI and dendritic loss seen in MDD.

Preterm-birth alters the development of nodal clustering and neural connection pattern in brain structural network at term-equivalent age

Preterm-born neonates are prone to impaired neurodevelopment that may be associated with disrupted whole-brain structural connectivity. The present study aimed to investigate the longitudinal developmental pattern of the structural network from preterm birth to term-equivalent age (TEA), and identify how prematurity influences the network topological organization and properties of local brain regions. Multi-shell diffusion-weighted MRI of 28 preterm-born scanned a short time after birth (PB-AB) and at TEA (PB-TEA), and 28 matched term-born (TB) neonates in the Developing Human Connectome Project (dHCP) were used to construct structural networks through constrained spherical deconvolution tractography. Structural network development from preterm birth to TEA showed reduced shortest path length, clustering coefficient, and modularity, and more "connector" hubs linking disparate communities. Furthermore, compared with TB newborns, premature birth significantly altered the nodal properties (i.e., clustering coefficient, within-module degree, and participation coefficient) in the limbic/paralimbic, default-mode, and subcortical systems but not global topology at TEA, and we were able to distinguish the PB from TB neonates at TEA based on the nodal properties with 96.43% accuracy. Our findings demonstrated a topological reorganization of the structural network occurs during the perinatal period that may prioritize the optimization of global network organization to form a more efficient architecture; and local topology was more vulnerable to premature birth-related factors than global organization of the structural network, which may underlie the impaired cognition and behavior in PB infants.

Indirect evidence for altered dopaminergic neurotransmission in very premature-born adults

While animal models indicate altered brain dopaminergic neurotransmission after premature birth, corresponding evidence in humans is scarce due to missing molecular imaging studies. To overcome this limitation, we studied dopaminergic neurotransmission changes in human prematurity indirectly by evaluating the spatial co-localization of regional alterations in blood oxygenation fluctuations with the distribution of adult dopaminergic neurotransmission. The study cohort comprised 99 very premature-born (<32 weeks of gestation and/or birth weight below 1500 g) and 107 full-term born young adults, being assessed by resting-state functional MRI (rs-fMRI) and IQ testing. Normative molecular imaging dopamine neurotransmission maps were derived from independent healthy control groups. We computed the co-localization of local (rs-fMRI) activity alterations in premature-born adults with respect to term-born individuals to different measures of dopaminergic neurotransmission. We performed selectivity analyses regarding other neuromodulatory systems and MRI measures. In addition, we tested if the strength of the co-localization is related to perinatal measures and IQ. We found selectively altered co-localization of rs-fMRI activity in the premature-born cohort with dopamine-2/3-receptor availability in premature-born adults. Alterations were specific for the dopaminergic system but not for the used MRI measure. The strength of the co-localization was negatively correlated with IQ. In line with animal studies, our findings support the notion of altered dopaminergic neurotransmission in prematurity which is associated with cognitive performance.

Network controllability of structural connectomes in the neonatal brain

White matter connectivity supports diverse cognitive demands by efficiently constraining dynamic brain activity. This efficiency can be inferred from network controllability, which represents the ease with which the brain moves between distinct mental states based on white matter connectivity. However, it remains unclear how brain networks support diverse functions at birth, a time of rapid changes in connectivity. Here, we investigate the development of network controllability during the perinatal period and the effect of preterm birth in 521 neonates. We provide evidence that elements of controllability are exhibited in the infant's brain as early as the third trimester and develop rapidly across the perinatal period. Preterm birth disrupts the development of brain networks and altered the energy required to drive state transitions at different levels. In addition, controllability at birth is associated with cognitive ability at 18 months. Our results suggest network controllability develops rapidly during the perinatal period to support cognitive demands but could be altered by environmental impacts like preterm birth.

Reduced neurite density index in the prefrontal cortex of adults with autism assessed using neurite orientation dispersion and density imaging

Background

Core symptoms of autism-spectrum disorder (ASD) have been associated with prefrontal cortex abnormalities. However, the mechanisms behind the observation remain incomplete, partially due to the challenges of modeling complex gray matter (GM) structures. This study aimed to identify GM microstructural alterations in adults with ASD using neurite orientation dispersion and density imaging (NODDI) and voxel-wise GM-based spatial statistics (GBSS) to reduce the partial volume effects from the white matter and cerebrospinal fluid.

Materials and methods

A total of 48 right-handed participants were included, of which 22 had ASD (17 men; mean age, 34.42 ± 8.27 years) and 26 were typically developing (TD) individuals (14 men; mean age, 32.57 ± 9.62 years). The metrics of NODDI (neurite density index [NDI], orientation dispersion index [ODI], and isotropic volume fraction [ISOVF]) were compared between groups using GBSS. Diffusion tensor imaging (DTI) metrics and surface-based cortical thickness were also compared. The associations between magnetic resonance imaging-based measures and ASD-related scores, including ASD-spectrum quotient, empathizing quotient, and systemizing quotient were also assessed in the region of interest (ROI) analysis.

Results

After controlling for age, sex, and intracranial volume, GBSS demonstrated significantly lower NDI in the ASD group than in the TD group in the left prefrontal cortex (caudal middle frontal, lateral orbitofrontal, pars orbitalis, pars triangularis, rostral middle frontal, and superior frontal region). In the ROI analysis of individuals with ASD, a significantly positive correlation was observed between the NDI in the left rostral middle frontal, superior frontal, and left frontal pole and empathizing quotient score. No significant between-group differences were observed in all DTI metrics, other NODDI (i.e., ODI and ISOVF) metrics, and cortical thickness.

Conclusion

GBSS analysis was used to demonstrate the ability of NODDI metrics to detect GM microstructural alterations in adults with ASD, while no changes were detected using DTI and cortical thickness evaluation. Specifically, we observed a reduced neurite density index in the left prefrontal cortices associated with reduced empathic abilities.

Association of Cortical and Subcortical Microstructure With Clinical Progression and Fluid Biomarkers in Patients With Parkinson Disease

BACKGROUND AND OBJECTIVES

Mean diffusivity (MD) of diffusion MRI (dMRI) has been used to measure cortical and subcortical microstructural properties. This study investigated relationships of cortical and subcortical MD, clinical progression, and fluid biomarkers in Parkinson disease (PD).

METHODS

This longitudinal study using data from the Parkinson's Progression Markers Initiative was collected from April 2011 to July 2022. Clinical symptoms were assessed with Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (UPDRS) and Montreal Cognitive Assessment (MoCA) scores. Clinical assessments were followed up to 5 years. Linear mixed-effects (LME) models were performed to examine associations of MD and the annual rate of changes in clinical scores. Partial correlation analysis was conducted to examine the associations of MD and fluid biomarker levels.

RESULTS

A total of 174 patients with PD (age 61.9 ± 9.7 years, 63% male) with baseline dMRI and at least 2 years of clinical follow-up were included. Results of LME models revealed a significant association between MD values, predominantly in subcortical regions, temporal lobe, occipital lobe, and frontal lobe, and annual rate of changes in clinical scores (UPDRS-Part-I, standardized β > 2.35; UPDRS-Part-II, standardized β > 2.34; postural instability and gait disorder score, standardized β > 2.47; MoCA, standardized β < -2.42; all p < 0.05, false discovery rate [FDR] corrected). In addition, MD was associated with the levels of neurofilament light chain in serum (r > 0.22) and α-synuclein (right putamen r = 0.31), β-amyloid 1-42 (left hippocampus r = -0.30), phosphorylated tau at 181 threonine position (r > 0.26), and total tau (r > 0.23) in CSF at baseline (all p < 0.05, FDR corrected). Furthermore, the β coefficients derived from MD and annual rate of changes in the clinical score recapitulated the spatial distribution of dopamine (DAT, D1, and D2), glutamate (mGluR5 and NMDA), serotonin (5-HT1a and 5-HT2a), cannabinoid (CB1), and γ-amino butyric acid A receptor neurotransmitter receptors/transporters (p < 0.05, FDR corrected) derived from PET scans in the brain of healthy volunteers.

DISCUSSION

In this cohort study, cortical and subcortical MD values at baseline were associated with clinical progression and baseline fluid biomarkers, suggesting that microstructural properties could be useful for stratification of patients with fast clinical progression.

Music impacts brain cortical microstructural maturation in very preterm infants: A longitudinal diffusion MR imaging study

Preterm birth disrupts important neurodevelopmental processes occurring from mid-fetal to term-age. Musicotherapy, by enriching infants' sensory input, might enhance brain maturation during this critical period of activity-dependent plasticity. To study the impact of music on preterm infants' brain structural changes, we recruited 54 very preterm infants randomized to receive or not a daily music intervention, that have undergone a longitudinal multi-shell diffusion MRI acquisition, before the intervention (at 33 weeks' gestational age) and after it (at term-equivalent-age). Using whole-brain fixel-based (FBA) and NODDI analysis (n = 40), we showed a longitudinal increase of fiber cross-section (FC) and fiber density (FD) in all major cerebral white matter fibers. Regarding cortical grey matter, FD decreased while FC and orientation dispersion index (ODI) increased, reflecting intracortical multidirectional complexification and intracortical myelination. The music intervention resulted in a significantly higher longitudinal increase of FC and ODI in cortical paralimbic regions, namely the insulo-orbito-temporopolar complex, precuneus/posterior cingulate gyrus, as well as the auditory association cortex. Our results support a longitudinal early brain macro and microstructural maturation of white and cortical grey matter in preterm infants. The music intervention led to an increased intracortical complexity in regions important for socio-emotional development, known to be impaired in preterm infants.

Preterm birth accelerates the maturation of spontaneous and resting activity in the visual cortex

Prematurity is among the leading risks for poor neurocognitive outcomes. The brains of preterm infants show alterations in structure and electrical activity, but the underlying circuit mechanisms are unclear. To address this, we performed a cross-species study of the electrophysiological activity in the visual cortices of prematurely born infants and mice. Using electroencephalography (EEG) in a sample of healthy preterm (N = 29) and term (N = 28) infants, we found that the maturation of the aperiodic EEG component was accelerated in the preterm cohort, with a significantly flatter 1/f slope when compared to the term infants. The flatter slope was a result of decreased spectral power in the theta and alpha bands and was correlated with the degree of prematurity. To determine the circuit and cellular changes that potentially mediate the changes in 1/f slope after preterm birth, we used in vivo electrophysiology in preterm mice and found that, similar to infants, preterm birth results in a flattened 1/f slope. We analyzed neuronal activity in the visual cortex of preterm (N = 6) and term (N = 9) mice and found suppressed spontaneous firing of neurons. Using immunohistochemistry, we further found an accelerated maturation of inhibitory circuits. In both preterm mice and infants, the functional maturation of the cortex was accelerated, underscoring birth as a critical checkpoint in cortical maturation. Our study points to a potential mechanism of preterm birth-related changes in resting neural activity, highlighting the utility of a cross-species approach in studying the neural circuit mechanisms of preterm birth-related neurodevelopmental conditions.

Altered Gray Matter Cortical and Subcortical T1-Weighted/T2-Weighted Ratio in Premature-Born Adults

BACKGROUND

Microscopic studies in newborns and animal models indicate impaired myelination after premature birth, particularly for cortical myelination; however, it remains unclear whether such myelination impairments last into adulthood and, if so, are relevant for impaired cognitive performance. It has been suggested that the ratio of T1-weighted (T1w) and T2-weighted (T2w) magnetic resonance imaging signal intensity (T1w/T2w ratio) is a proxy for myelin content. We hypothesized altered gray matter (GM) T1w/T2w ratio in premature-born adults, which is associated with lower cognitive performance after premature birth.

METHODS

We analyzed GM T1w/T2w ratio in 101 adults born very premature (VP) and/or at very low birth weight (VLBW) (<32 weeks of gestation and/or birth weight <1500 g) and 109 full-term control subjects at 26 years of age, controlled for voxelwise volume alterations. Cognitive performance was assessed by verbal, performance, and full scale IQ using the Wechsler Adult Intelligence Scale.

RESULTS

Significantly higher T1w/T2w ratio in VP/VLBW subjects was found bilaterally in widespread cortical areas, particularly in frontal, parietal, and temporal cortices, and in putamen and pallidum. In these areas, T1w/T2w ratio was not related to birth variables, such as gestational age, or IQ scores. In contrast, significantly lower T1w/T2w ratio in VP/VLBW subjects was found in bilateral clusters in superior temporal gyrus, which was associated with birth weight in the VP/VLBW group. Furthermore, lower T1w/T2w ratio in left superior temporal gyrus was associated with lower full scale and verbal IQ.

CONCLUSIONS

Results demonstrate GM T1w/T2w ratio alterations in premature-born adults and suggest altered GM myelination development after premature birth with lasting and functionally relevant effects into early adulthood.

Applications of advanced diffusion MRI in early brain development: a comprehensive review

Brain development follows a protracted developmental timeline with foundational processes of neurodevelopment occurring from the third trimester of gestation into the first decade of life. Defining structural maturational patterns of early brain development is a critical step in detecting divergent developmental trajectories associated with neurodevelopmental and psychiatric disorders that arise later in life. While considerable advancements have already been made in diffusion magnetic resonance imaging (dMRI) for pediatric research over the past three decades, the field of neurodevelopment is still in its infancy with remarkable scientific and clinical potential. This comprehensive review evaluates the application, findings, and limitations of advanced dMRI methods beyond diffusion tensor imaging, including diffusion kurtosis imaging (DKI), constrained spherical deconvolution (CSD), neurite orientation dispersion and density imaging (NODDI) and composite hindered and restricted model of diffusion (CHARMED) to quantify the rapid and dynamic changes supporting the underlying microstructural architectural foundations of the brain in early life.

Breast Milk Exposure is Associated With Cortical Maturation in Preterm Infants

OBJECTIVE

Breast milk exposure is associated with improved neurocognitive outcomes following preterm birth but the neural substrates linking breast milk with outcome are uncertain. We tested the hypothesis that high versus low breast milk exposure in preterm infants results in cortical morphology that more closely resembles that of term-born infants.

METHODS

We studied 135 preterm (<32 weeks' gestation) and 77 term infants. Feeding data were collected from birth until hospital discharge and brain magnetic resonance imaging (MRI) was performed at term-equivalent age. Cortical indices (volume, thickness, surface area, gyrification index, sulcal depth, and curvature) and diffusion parameters (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD], axial diffusivity [AD], neurite density index [NDI], and orientation dispersion index [ODI]) were compared between preterm infants who received exclusive breast milk for <75% of inpatient days, preterm infants who received exclusive breast milk for ≥75% of inpatient days and term-born controls. To investigate a dose response effect, we performed linear regression using breast milk exposure quartile weighted by propensity scores.

RESULTS

In preterm infants, high breast milk exposure was associated with reduced cortical gray matter volume (d = 0.47, 95% confidence interval [CI] = 0.14 to 0.94, p = 0.014), thickness (d = 0.42, 95% CI = 0.08 to 0.84, p = 0.039), and RD (d = 0.38, 95% CI = 0.002 to 0.77, p = 0.039), and increased FA (d = -0.38, 95% CI = -0.74 to -0.01, p = 0.037) after adjustment for age at MRI, which was similar to the cortical phenotype observed in term-born controls. Breast milk exposure quartile was associated with cortical volume (ß = -0.192, 95% CI = -0.342 to -0.042, p = 0.017), FA (ß = 0.223, 95% CI = 0.075 to 0.372, p = 0.007), and RD (ß = -0.225, 95% CI = -0.373 to -0.076, p = 0.007) following adjustment for age at birth, age at MRI, and weighted by propensity scores, suggesting a dose effect.

INTERPRETATION

High breast milk exposure following preterm birth is associated with a cortical imaging phenotype that more closely resembles the brain morphology of term-born infants and effects appear to be dose-dependent. ANN NEUROL 2023;93:591-603.

Postnatal serum IGF-1 levels associate with brain volumes at term in extremely preterm infants

BACKGROUND

Growth factors important for normal brain development are low in preterm infants. This study investigated the link between growth factors and preterm brain volumes at term.

MATERIAL/METHODS

Infants born <28 weeks gestational age (GA) were included. Endogenous levels of insulin-like growth factor (IGF)-1, brain-derived growth factor, vascular endothelial growth factor, and platelet-derived growth factor (expressed as area under the curve [AUC] for serum samples from postnatal days 1, 7, 14, and 28) were utilized in a multivariable linear regression model. Brain volumes were determined by magnetic resonance imaging (MRI) at term equivalent age.

RESULTS

In total, 49 infants (median [range] GA 25.4 [22.9-27.9] weeks) were included following MRI segmentation quality assessment and AUC calculation. IGF-1 levels were independently positively associated with the total brain (p < 0.001, β = 0.90), white matter (p = 0.007, β = 0.33), cortical gray matter (p = 0.002, β = 0.43), deep gray matter (p = 0.008, β = 0.05), and cerebellar (p = 0.006, β = 0.08) volume adjusted for GA at birth and postmenstrual age at MRI. No associations were seen for other growth factors.

CONCLUSIONS

Endogenous exposure to IGF-1 during the first 4 weeks of life was associated with total and regional brain volumes at term. Optimizing levels of IGF-1 might improve brain growth in extremely preterm infants.

IMPACT

High serum levels of insulin-like growth factor (IGF)-1 during the first month of life were independently associated with increased total brain volume, white matter, gray matter, and cerebellar volume at term equivalent age in extremely preterm infants. IGF-1 is a critical regulator of neurodevelopment and postnatal levels are low in preterm infants. The effects of IGF-1 levels on brain development in extremely preterm infants are not fully understood. Optimizing levels of IGF-1 may benefit early brain growth in extremely preterm infants. The effects of systemically administered IGF-1/IGFBP3 in extremely preterm infants are now being investigated in a randomized controlled trial (Clinicaltrials.gov: NCT03253263).

Spatiotemporal Developmental Gradient of Thalamic Morphology, Microstructure, and Connectivity fromthe Third Trimester to Early Infancy

Thalamus is a critical component of the limbic system that is extensively involved in both basic and high-order brain functions. However, how the thalamic structure and function develops at macroscopic and microscopic scales during the perinatal period development is not yet well characterized. Here, we used multishell high-angular resolution diffusion MRI of 144 preterm-born and full-term infants in both sexes scanned at 32-44 postmenstrual weeks (PMWs) from the Developing Human Connectome Project database to investigate the thalamic development in morphology, microstructure, associated connectivity, and subnucleus division. We found evident anatomic expansion and linear increases of fiber integrity in the lateral side of thalamus compared with the medial part. The tractography results indicated that thalamic connection to the frontal cortex developed later than the other thalamocortical connections (parieto-occipital, motor, somatosensory, and temporal). Using a connectivity-based segmentation strategy, we revealed that functional partitions of thalamic subdivisions were formed at 32 PMWs or earlier, and the partition developed toward the adult pattern in a lateral-to-medial pattern. Collectively, these findings revealed faster development of the lateral thalamus than the central part as well as a posterior-to-anterior developmental gradient of thalamocortical connectivity from the third trimester to early infancy.SIGNIFICANCE STATEMENT This is the first study that characterizes the spatiotemporal developmental pattern of thalamus during the third trimester to early infancy. We found that thalamus develops in a lateral-to-medial pattern for both thalamic microstructures and subdivisions; and thalamocortical connectivity develops in a posterior-to-anterior gradient that thalamofrontal connectivity appears later than the other thalamocortical connections. These findings may enrich our understanding of the developmental principles of thalamus and provide references for the atypical brain growth in neurodevelopmental disorders.

Risk Factors of Language Delay at Two Years of Corrected Age among Very-Low-Birth-Weight Preterm Infants: A Population-Based Study

Language delays are often underestimated in very-low-birth-weight (VLBW) preterm infants. We aimed to identify the risk factors of language delay at two years of corrected age in this vulnerable population. VLBW infants, who were assessed at two years of corrected age using the Bayley Scale of Infant Development, third edition, were included using a population-based cohort database. Language delay was defined as mild to moderate if the composite score was between 70 and 85 and severe if the score was < 70. Multivariable logistic regression analysis was used to identify the perinatal risk factors associated with language delay. The study comprised 3797 VLBW preterm infants; 678 (18%) had a mild to moderate delay and 235 (6%) had a severe delay. After adjusting for confounding factors, low maternal education level, low maternal socioeconomic status, extremely low birth weight, male sex, and severe intraventricular hemorrhage (IVH) and/or cystic periventricular leukomalacia (PVL) were found to be significantly associated with both mild to moderate and severe delays. Resuscitation at delivery, necrotizing enterocolitis, and patent ductus arteriosus requiring ligation showed significant associations with severe delay. The strongest factors predicting both mild to moderate and severe language delays were the male sex and severe IVH and/or cystic PVL; thus, early targeted intervention is warranted in these populations.

Progressive structural and covariance connectivity abnormalities in patients with Alzheimer's disease

Background

Alzheimer's disease (AD) is one of most prevalent neurodegenerative diseases worldwide and characterized by cognitive decline and brain structure atrophy. While studies have reported substantial grey matter atrophy related to progression of AD, it remains unclear about brain regions with progressive grey matter atrophy, covariance connectivity, and the associations with cognitive decline in AD patients.

Objective

This study aims to investigate the grey matter atrophy, structural covariance connectivity abnormalities, and the correlations between grey matter atrophy and cognitive decline during AD progression.

Materials

We analyzed neuroimaging data of healthy controls (HC, n = 45) and AD patients (n = 40) at baseline (AD-T1) and one-year follow-up (AD-T2) obtained from the Alzheimer's Disease Neuroimaging Initiative. We investigated AD-related progressive changes of grey matter volume, covariance connectivity, and the clinical relevance to further understand the pathological progression of AD.

Results

The results showed clear patterns of grey matter atrophy in inferior frontal gyrus, prefrontal cortex, lateral temporal gyrus, posterior cingulate cortex, insula, hippocampus, caudate, and thalamus in AD patients. There was significant atrophy in bilateral superior temporal gyrus (STG) and left caudate in AD patients over a one-year period, and the grey matter volume decrease in right STG and left caudate was correlated with cognitive decline. Additionally, we found reduced structural covariance connectivity between right STG and left caudate in AD patients. Using AD-related grey matter atrophy as features, there was high discrimination accuracy of AD patients from HC, and AD patients at different time points.

Altered cortical microstructure in preterm infants at term-equivalent age relative to term-born neonates

Preterm (PT) birth is a potential factor for abnormal brain development. Although various alterations of cortical structure and functional connectivity in preterm infants have been reported, the underlying microstructural foundation is still undetected thoroughly in PT infants relative to full-term (FT) neonates. To detect the very early cortical microstructural alteration noninvasively with advanced neurite orientation dispersion and density imaging (NODDI) on a whole-brain basis, we used multi-shell diffusion MRI of healthy newborns selected from the Developing Human Connectome Project. 73 PT infants and 69 FT neonates scanned at term-equivalent age were included in this study. By extracting the core voxels of gray matter (GM) using GM-based spatial statistics (GBSS), we found that comparing to FT neonates, infants born preterm showed extensive lower neurite density in both primary and higher-order association cortices (FWE corrected, P < 0.025). Higher orientation dispersion was only found in very preterm subgroup in the orbitofrontal cortex, fronto-insular cortex, entorhinal cortex, a portion of posterior cingular gyrus, and medial parieto-occipital cortex. This study provided new insights into exploring structural MR for functional and behavioral variations in preterm population, and these findings may have marked clinical importance, particularly in the guidance of ameliorating the development of premature brain.

Aberrant claustrum structure in preterm-born neonates: an MRI study

The human claustrum is a gray matter structure in the white matter between insula and striatum. Previous analysis found altered claustrum microstructure in very preterm-born adults associated with lower cognitive performance. As the claustrum development is related to hypoxia-ischemia sensitive transient cell populations being at-risk in premature birth, we hypothesized that claustrum structure is already altered in preterm-born neonates. We studied anatomical and diffusion-weighted MRIs of 83 preterm- and 83 term-born neonates at term-equivalent age. Additionally, claustrum development was analyzed both in a spectrum of 377 term-born neonates and longitudinally in 53 preterm-born subjects. Data was provided by the developing Human Connectome Project. Claustrum development showed increasing volume, increasing fractional anisotropy (FA), and decreasing mean diffusivity (MD) around term both across term- and preterm-born neonates. Relative to term-born ones, preterm-born neonates had (i) increased absolute and relative claustrum volumes, both indicating increased cellular and/or extracellular matter and being in contrast to other subcortical gray matter regions of decreased volumes such as thalamus; (ii) lower claustrum FA and higher claustrum MD, pointing at increased extracellular matrix and impaired axonal integrity; and (iii) aberrant covariance between claustrum FA and MD, respectively, and that of distributed gray matter regions, hinting at relatively altered claustrum microstructure. Results together demonstrate specifically aberrant claustrum structure in preterm-born neonates, suggesting altered claustrum development in prematurity, potentially relevant for later cognitive performance.

Cyto/myeloarchitecture of cortical gray matter and superficial white matter in early neurodevelopment: multimodal MRI study in preterm neonates

The cerebral cortex undergoes rapid microstructural changes throughout the third trimester. Recently, there has been growing interest on imaging features that represent cyto/myeloarchitecture underlying intracortical myelination, cortical gray matter (GM), and its adjacent superficial whitematter (sWM). Using 92 magnetic resonance imaging scans from 78 preterm neonates, the current study used combined T1-weighted/T2-weighted (T1w/T2w) intensity ratio and diffusion tensor imaging (DTI) measurements, including fractional anisotropy (FA) and mean diffusivity (MD), to characterize the developing cyto/myeloarchitectural architecture. DTI metrics showed a linear trajectory: FA decreased in GM but increased in sWM with time; and MD decreased in both GM and sWM. Conversely, T1w/T2w measurements showed a distinctive parabolic trajectory, revealing additional cyto/myeloarchitectural signature inferred. Furthermore, the spatiotemporal courses were regionally heterogeneous: central, ventral, and temporal regions of GM and sWM exhibited faster T1w/T2w changes; anterior sWM areas exhibited faster FA increases; and central and cingulate areas in GM and sWM exhibited faster MD decreases. These results may explain cyto/myeloarchitectural processes, including dendritic arborization, synaptogenesis, glial proliferation, and radial glial cell organization and apoptosis. Finally, T1w/T2w values were significantly associated with 1-year language and cognitive outcome scores, while MD significantly decreased with intraventricular hemorrhage.

Vulnerability of the Neonatal Connectome following Postnatal Stress

Stress following preterm birth can disrupt the emerging foundation of the neonatal brain. The current study examined how structural brain development is affected by a stressful early environment and whether changes in topological architecture at term-equivalent age could explain the increased vulnerability for behavioral symptoms during early childhood. Longitudinal changes in structural brain connectivity were quantified using diffusion-weighted imaging (DWI) and tractography in preterm born infants (gestational age <28 weeks), imaged at 30 and/or 40 weeks of gestation (N = 145, 43.5% female). A global index of postnatal stress was determined based on the number of invasive procedures during hospitalization (e.g., heel lance). Higher stress levels impaired structural connectivity growth in a subnetwork of 48 connections (p = 0.003), including the amygdala, insula, hippocampus, and posterior cingulate cortex. Findings were replicated in an independent validation sample (N = 123, 39.8% female, n = 91 with follow-up). Classifying infants into vulnerable and resilient based on having more or less internalizing symptoms at two to five years of age (n = 71) revealed lower connectivity in the hippocampus and amygdala for vulnerable relative to resilient infants (p < 0.001). Our findings suggest that higher stress exposure during hospital admission is associated with slower growth of structural connectivity. The preservation of global connectivity of the amygdala and hippocampus might reflect a stress-buffering or resilience-enhancing factor against a stressful early environment and early-childhood internalizing symptoms.SIGNIFICANCE STATEMENT The preterm brain is exposed to various external stimuli following birth. The effects of early chronic stress on neonatal brain networks and the remarkable degree of resilience are not well understood. The current study aims to provide an increased understanding of the impact of postnatal stress on third-trimester brain development and describe the topological architecture of a resilient brain. We observed a sparser neonatal brain network in infants exposed to higher postnatal stress. Limbic regulatory regions, including the hippocampus and amygdala, may play a key role as crucial convergence sites of protective factors. Understanding how stress-induced alterations in early brain development might lead to brain (re)organization may provide essential insights into resilient functioning.

Early structural connectivity within the sensorimotor network: Deviations related to prematurity and association to neurodevelopmental outcome

Consisting of distributed and interconnected structures that interact through cortico-cortical connections and cortico-subcortical loops, the sensorimotor (SM) network undergoes rapid maturation during the perinatal period and is thus particularly vulnerable to preterm birth. However, the impact of prematurity on the development and integrity of the emerging SM connections and their relationship to later motor and global impairments are still poorly understood. In this study we aimed to explore to which extent the early microstructural maturation of SM white matter (WM) connections at term-equivalent age (TEA) is modulated by prematurity and related with neurodevelopmental outcome at 18 months corrected age. We analyzed 118 diffusion MRI datasets from the developing Human Connectome Project (dHCP) database: 59 preterm (PT) low-risk infants scanned near TEA and a control group of full-term (FT) neonates paired for age at MRI and sex. We delineated WM connections between the primary SM cortices (S1, M1 and paracentral region) and subcortical structures using probabilistic tractography, and evaluated their microstructure with diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) models. To go beyond tract-specific univariate analyses, we computed a maturational distance related to prematurity based on the multi-parametric Mahalanobis distance of each PT infant relative to the FT group. Our results confirmed the presence of microstructural differences in SM tracts between PT and FT infants, with effects increasing with lower gestational age at birth. Maturational distance analyses highlighted that prematurity has a differential effect on SM tracts with higher distances and thus impact on (i) cortico-cortical than cortico-subcortical connections; (ii) projections involving S1 than M1 and paracentral region; and (iii) the most rostral cortico-subcortical tracts, involving the lenticular nucleus. These different alterations at TEA suggested that vulnerability follows a specific pattern coherent with the established WM caudo-rostral progression of maturation. Finally, we highlighted some relationships between NODDI-derived maturational distances of specific tracts and fine motor and cognitive outcomes at 18 months. As a whole, our results expand understanding of the significant impact of premature birth and early alterations on the emerging SM network even in low-risk infants, with possible relationship with neurodevelopmental outcomes. This encourages further exploration of these potential neuroimaging markers for prediction of neurodevelopmental disorders, with special interest for subtle neuromotor impairments frequently observed in preterm-born children.

Montelukast reduces grey matter abnormalities and functional deficits in a mouse model of inflammation-induced encephalopathy of prematurity

Encephalopathy of prematurity (EoP) affects approximately 30% of infants born < 32 weeks gestation and is highly associated with inflammation in the foetus. Here we evaluated the efficacy of montelukast, a cysteinyl leukotriene receptor antagonist widely used to treat asthma in children, to ameliorate peripheral and central inflammation, and subsequent grey matter neuropathology and behaviour deficits in a mouse model of EoP. Male CD-1 mice were treated with intraperitoneal (i.p.) saline or interleukin-1beta (IL-1β, 40 μg/kg, 5 μL/g body weight) from postnatal day (P)1-5 ± concomitant montelukast (1-30 mg/kg). Saline or montelukast treatment was continued for a further 5 days post-injury. Assessment of systemic and central inflammation and short-term neuropathology was performed from 4 h following treatment through to P10. Behavioural testing, MRI and neuropathological assessments were made on a second cohort of animals from P36 to 54. Montelukast was found to attenuate both peripheral and central inflammation, reducing the expression of pro-inflammatory molecules (IL-1β, IL-6, TNF) in the brain. Inflammation induced a reduction in parvalbumin-positive interneuron density in the cortex, which was normalised with high-dose montelukast. The lowest effective dose, 3 mg/kg, was able to improve anxiety and spatial learning deficits in this model of inflammatory injury, and alterations in cortical mean diffusivity were not present in animals that received this dose of montelukast. Repurposed montelukast administered early after preterm birth may, therefore, improve grey matter development and outcome in EoP.

Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease

Introduction

Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET).

Methods

Seventy-one participants underwent multi-shell diffusion MRI, 18F-THK5351 PET, 11C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores.

Results

In AD-S group, there was a significant positive correlation between FW and 18F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F-THK5351 and cognitive function in the same regions.

Discussion

FW imaging could be a biomarker for tau in AD alongside clinical correlations.

Concurrent mapping of brain ontogeny and phylogeny within a common space: Standardized tractography and applications

Developmental and evolutionary effects on brain organization are complex, yet linked, as evidenced by the correspondence in cortical area expansion across these vastly different time scales. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric measurements. Here, we propose a novel framework that allows the integration of structural connectivity maps from humans (adults and neonates) and nonhuman primates (macaques) onto a common space. We use white matter bundles to anchor the common space and use the uniqueness of cortical connection patterns to these bundles to probe area specialization. This enabled us to quantitatively study divergences and similarities in connectivity over evolutionary and developmental scales, to reveal brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains. Our findings open new avenues for an integrative approach to imaging neuroanatomy.

Brain Development and Maternal Behavior in Relation to Cognitive and Language Outcomes in Preterm-Born Children

BACKGROUND

Children born very preterm (≤32 weeks gestational age) show poorer cognitive and language development compared with their term-born peers. The importance of supportive maternal responses to the child's cues for promoting neurodevelopment is well established. However, little is known about whether supportive maternal behavior can buffer the association of early brain dysmaturation with cognitive and language performance.

METHODS

Infants born very preterm (N = 226) were recruited from the neonatal intensive care unit for a prospective, observational cohort study. Chart review (e.g., size at birth, postnatal infection) was conducted from birth to discharge. Magnetic resonance imaging, including diffusion tensor imaging, was acquired at approximately 32 weeks postmenstrual age and again at term-equivalent age. Fractional anisotropy, a quantitative measure of brain maturation, was obtained from 11 bilateral regions of interest in the cortical gray matter. At 3 years (n = 187), neurodevelopmental testing (Bayley Scales of Infant and Toddler Development-III) was administered, and parent-child interaction was filmed. Maternal behavior was scored using the Emotional Availability Scale-IV. A total of 146 infants with neonatal brain imaging and follow-up data were included for analysis. Generalized estimating equations were used to examine whether maternal support interacted with mean fractional anisotropy values to predict Cognitive and Language scores at 3 years, accounting for confounding neonatal and maternal factors.

RESULTS

Higher maternal support significantly moderated cortical fractional anisotropy values at term-equivalent age to predict higher Cognitive (interaction term β = 2.01, p = .05) and Language (interaction term β = 1.85, p = .04) scores.

CONCLUSIONS

Findings suggest that supportive maternal behavior following early brain dysmaturation may provide an opportunity to promote optimal neurodevelopment in children born very preterm.

Differentiate preterm and term infant brains and characterize the corresponding biomarkers via DICCCOL-based multi-modality graph neural networks

Preterm birth is a worldwide problem that affects infants throughout their lives significantly. Therefore, differentiating brain disorders, and further identifying and characterizing the corresponding biomarkers are key issues to investigate the effects of preterm birth, which facilitates the interventions for neuroprotection and improves outcomes of prematurity. Until now, many efforts have been made to study the effects of preterm birth; however, most of the studies merely focus on either functional or structural perspective. In addition, an effective framework not only jointly studies the brain function and structure at a group-level, but also retains the individual differences among the subjects. In this study, a novel dense individualized and common connectivity-based cortical landmarks (DICCCOL)-based multi-modality graph neural networks (DM-GNN) framework is proposed to differentiate preterm and term infant brains and characterize the corresponding biomarkers. This framework adopts the DICCCOL system as the initialized graph node of GNN for each subject, utilizing both functional and structural profiles and effectively retaining the individual differences. To be specific, functional magnetic resonance imaging (fMRI) of the brain provides the features for the graph nodes, and brain fiber connectivity is utilized as the structural representation of the graph edges. Self-attention graph pooling (SAGPOOL)-based GNN is then applied to jointly study the function and structure of the brain and identify the biomarkers. Our results successfully demonstrate that the proposed framework can effectively differentiate the preterm and term infant brains. Furthermore, the self-attention-based mechanism can accurately calculate the attention score and recognize the most significant biomarkers. In this study, not only 87.6% classification accuracy is observed for the developing Human Connectome Project (dHCP) dataset, but also distinguishing features are explored and extracted. Our study provides a novel and uniform framework to differentiate brain disorders and characterize the corresponding biomarkers.

Cortical gray matter microstructural alterations in patients with type 2 diabetes mellitus

BACKGROUND AND PURPOSE

Neurodegenerative processes are widespread in the brains of type 2 diabetes mellitus (T2DM) patients; gaps remain to exist in the current knowledge of the associated gray matter (GM) microstructural alterations.

METHODS

A cross-sectional study was conducted to investigate alterations in GM microarchitecture in T2DM patients by diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI). Seventy-eight T2DM patients and seventy-four age-, sex-, and education level-matched healthy controls (HCs) without cognitive impairment were recruited. Cortical macrostructure and GM microstructure were assessed by surface-based analysis and GM-based spatial statistics (GBSS), respectively. Machine learning models were trained to evaluate the diagnostic values of cortical intracellular volume fraction (ICVF) for the classification of T2DM versus HCs.

RESULTS

There were no differences in cortical thickness or area between the groups. GBSS analysis revealed similar GM microstructural patterns of significantly decreased fractional anisotropy, increased mean diffusivity and radial diffusivity in T2DM patients involving the frontal and parietal lobes, and significantly lower ICVF values were observed in nearly all brain regions of T2DM patients. A support vector machine model with a linear kernel was trained to realize the T2DM versus HC classification and exhibited the highest performance among the trained models, achieving an accuracy of 74% and an area under the curve of 83%.

CONCLUSIONS

NODDI may help to probe the widespread GM neuritic density loss in T2DM patients occurs before measurable macrostructural alterations. The cortical ICVF values may provide valuable diagnostic information regarding the early GM microstructural alterations in T2DM.

Developmental pattern of association fibers and their interaction with associated cortical microstructures in 0-5-month-old infants

Association fibers connect the cortical regions and experience rapid development involving myelination and axonal growth during infancy. Yet, the spatiotemporal patterns of microstructural changes along these tracts, as well as the developmental interaction between the white matter (WM) tracts and the cortical gray matter (cGM) connected to them, are mostly unknown during infancy. In this study, we performed a diffusion MRI-based tractography and microstructure study in a cohort of 89 healthy preterm-born infants with gestational age at birth between 28.1∼36.4 weeks and postmenstrual age at scan between 39.9∼59.9 weeks. Results revealed that several C-shaped fibers, such as the arcuate fasciculus, cingulum, and uncinate fasciculus, demonstrated symmetrical along-tract profiles; and the horizontally oriented running fibers, including the inferior fronto-occipital fasciculus and the inferior longitudinal fasciculus, demonstrated an anterior-posterior developmental gradient. This study characterized the along-tract profiles using fixel-based analysis and revealed that the fiber cross-section (FC) of all five association fibers demonstrated a fluctuating increase with age, while the fiber density (FD) monotonically increase with age. NODDI was utilized to analyze the microstructural development of cGM and indicated cGM connected to the anterior end of the association fibers developed faster than that of the posterior end during 0-5 months. Notably, a mediation analysis was used to explore the relation between the development of WM and associated cGM, and demonstrated a partial mediation effect of FD in WM on the development of intracellular volume (ICV) in cGM and a full mediation effect of ICV on the growth of FD in most fibers, suggesting a predominant mediation of cGM on the WM development. Furthermore, for assessing whether those results were biased by prematurity, we compared preterm- and term-born neonates with matched scan age, gender, and multiple births from the developing human connectome project (dHCP) dataset to assess the effect of preterm-birth, and the results indicated a similar developmental pattern of the association fibers and their attached cGM. These findings presented a comprehensive picture of the major association fibers during early infancy and deciphered the developmental interaction between WM and cGM in this period.

Tract-specific white matter microstructural alterations in subjects with schizophrenia and unaffected first-degree relatives

White matter tracts alterations have been reported in schizophrenia (SZ), but whether such abnormalities are associated with the effects of the disorder itself and/or genetic vulnerability remains unclear. Moreover, the specific patterns of different parts of these altered tracts have been less well studied. Thus, diffusion-weighted images were acquired from 38 healthy controls (HCs), 48 schizophrenia patients, and 33 unaffected first-degree relatives of SZs (FDRs). Diffusion properties of the 25 major tracts automatically extracted with probabilistic tractography were calculated and compared among groups. Regarding the peripheral regions of the tracts, significantly higher diffusivity values in the left superior longitudinal fasciculus (SLF) and the left anterior thalamic radiation (ATR) were observed in SZs than in HCs and unaffected FDRs. However, there were no significant differences between HCs and FDRs in these two tracts. While no main effects of group with respect to the core regions of the 25 tracts survived multiple comparisons correction, FDRs had significantly higher diffusivity values in the left medial lemniscus and lower diffusivity values in the middle cerebellar peduncle than HCs and SZs. These findings enhance the understanding of the abnormal patterns in the peripheral and core regions of the tracts in SZs and those at high genetic risk for schizophrenia. Our results suggest that alterations in the peripheral regions of the left SLF and ATR are features of established illness rather than genetic predisposition, which may serve as critical neural substrates for the psychopathology of schizophrenia.